A Multi-Objective Optimal Torque Distribution Strategy for Four In-Wheel-Motor Drive Electric Vehicles

被引:37
作者
Lin, Cheng [1 ,2 ]
Liang, Sheng [1 ]
Chen, Jian [1 ]
Gao, Xiang [1 ]
机构
[1] Beijing Inst Technol, Natl Engn Lab Elect Vehicles, Beijing 100081, Peoples R China
[2] Beijing Inst Technol, Collaborat Innovat Ctr Elect Vehicles Beijing, Beijing 100081, Peoples R China
基金
中国国家自然科学基金;
关键词
Electric vehicles; torque distribution strategy; hybrid model predictive control (hMPC); multi-objective control; YAW STABILITY CONTROL; CONTROL ALLOCATION; STEERING CONTROL; MOTION CONTROL; FRONT; DYNAMICS; DESIGN;
D O I
10.1109/ACCESS.2019.2917313
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Since four in-wheel-motor drive electric vehicles (4IDEVs) are overactuated systems, the torque distribution strategy is crucial for improving the system efficiency, lateral stability, and safety. Hence, this paper proposes a multiobjective optimal torque distribution strategy for 4IDEVs to improve the vehicle yaw stability performance and energy efficiency. First, a motor energy loss model is built to describe the motor power loss characteristics, and an energy efficiency control allocation (EECA) method over the NEDC is proposed to analyze the model accuracy. Then, a hybrid model predictive control (hMPC)-based nonlinear yaw stability controller is employed to calculate the reference yaw moment and the active steering angle. Finally, a multiobjective controller is designed to minimize the drivetrain power loss while ensuring the vehicle stability, in which the four wheels torques are allocated to track the reference yaw moment. The proposed strategy is evaluated on the dSPACE-based platform over the single lane change test and fishhook steering test. The results indicate that the suggested torque distribution strategy can improve the vehicle stability on different conditions and the energy consumption is significantly reduced compared to an electric stability control (ESC) method.
引用
收藏
页码:64627 / 64640
页数:14
相关论文
共 32 条
[1]  
[Anonymous], 2017, P 2017 IEEE TRANSPOR, DOI DOI 10.1109/ITEC-AP.2017.8080801
[2]   Control of systems integrating logic, dynamics, and constraints [J].
Bemporad, A ;
Morari, M .
AUTOMATICA, 1999, 35 (03) :407-427
[3]  
Brembeck J, 2012, 2012 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), P322, DOI 10.1109/IVS.2012.6232147
[4]   ELECTRONIC STABILITY CONTROL FOR ELECTRIC VEHICLE WITH FOUR IN-WHEEL MOTORS [J].
Chen, B. -C. ;
Kuo, C. -C. .
INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY, 2014, 15 (04) :573-580
[5]  
Chen J., 2018, 10 INT C APPL EN HON
[6]   Design and Experimental Evaluations on Energy Efficient Control Allocation Methods for Overactuated Electric Vehicles: Longitudinal Motion Case [J].
Chen, Yan ;
Wang, Junmin .
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2014, 19 (02) :538-548
[7]   Fast and Global Optimal Energy-Efficient Control Allocation With Applications to Over-Actuated Electric Ground Vehicles [J].
Chen, Yan ;
Wang, Junmin .
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2012, 20 (05) :1202-1211
[8]   Design and Evaluation on Electric Differentials for Overactuated Electric Ground Vehicles With Four Independent In-Wheel Motors [J].
Chen, Yan ;
Wang, Junmin .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2012, 61 (04) :1534-1542
[9]   Model Predictive Control for Vehicle Yaw Stability With Practical Concerns [J].
Choi, Mooryong ;
Choi, Seibum B. .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2014, 63 (08) :3539-3548
[10]   Wheel Torque Distribution Criteria for Electric Vehicles With Torque-Vectoring Differentials [J].
De Novellis, Leonardo ;
Sorniotti, Aldo ;
Gruber, Patrick .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2014, 63 (04) :1593-1602